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In streaming data analysis, it is crucial to detect significant shifts in the data distribution or the accuracy of predictive models over time, a phenomenon known as **concept drift**. The **heimdall** package aims to identify when concept drift occurs and provide methodologies for adapting models in non-stationary environments. It offers a range of state-of-the-art techniques for detecting concept drift and maintaining model performance. Additionally, **heimdall** provides tools for adapting models in response to these changes, ensuring continuous and accurate predictions in dynamic contexts. Methods for concept drift detection are described in Tavares (2022) <doi:10.1007/s12530-021-09415-z>.
Version: | 1.0.737 |
Imports: | stats, caret, daltoolbox, ggplot2, reticulate, pROC, car |
Published: | 2025-04-28 |
DOI: | 10.32614/CRAN.package.heimdall |
Author: | Lucas Tavares [aut],
Leonardo Carvalho [aut],
Diego Carvalho [aut],
Esther Pacitti [aut],
Fabio Porto [aut],
Eduardo Ogasawara |
Maintainer: | Eduardo Ogasawara <eogasawara at ieee.org> |
License: | MIT + file LICENSE |
URL: | https://cefet-rj-dal.github.io/heimdall/, https://github.com/cefet-rj-dal/heimdall |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | heimdall results |
Reference manual: | heimdall.pdf |
Package source: | heimdall_1.0.737.tar.gz |
Windows binaries: | r-devel: heimdall_1.0.737.zip, r-release: heimdall_1.0.737.zip, r-oldrel: heimdall_1.0.717.zip |
macOS binaries: | r-release (arm64): heimdall_1.0.737.tgz, r-oldrel (arm64): heimdall_1.0.737.tgz, r-release (x86_64): heimdall_1.0.737.tgz, r-oldrel (x86_64): heimdall_1.0.737.tgz |
Old sources: | heimdall archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.